A recent BBC News article highlighted a shift in how information is discovered online.
Instead of lists of links, users are increasingly presented with AI-generated answers—summaries that extract and synthesise content from multiple sources.
For researchers and academic institutions, this raises an important question:
What happens when your work is no longer read in full—but interpreted by an AI system?
The focus is already shifting toward making content more “AI-friendly”:
- clearer structure
- concise phrasing
- easily extractable insights
All sensible developments.
But they don’t solve a more fundamental issue.
AI does not evaluate meaning in context.
It identifies patterns and generates plausible summaries.
So if a text is:
- slightly ambiguous
- loosely framed
- or open to interpretation
that ambiguity is not corrected. It is simply carried forward.
In academic communication, that has consequences.
Because accuracy is not just about what is written—
but how it is understood, cited, and reused.
AI may increase visibility.
But it also increases the importance of getting the original wording exactly right.
This is where careful human editing remains essential:
not to compete with AI, but to ensure that what it amplifies is precise, unambiguous, and true to the author’s intent.